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The sequence approach to organizational dynamics: Quantifying positive feedback mechanisms in employment trajectories
Stockholm University, Faculty of Social Sciences, Department of Sociology.ORCID iD: 0000-0003-2685-9238
(English)Manuscript (preprint) (Other academic)
Abstract [en]

In this study, we use Swedish longitudinal data on employment in the Stockholm Region to study the extent of positive feedback mechanisms in the structure and change of employment trajectories. We represent employment trajectories as sequences of yearly employment states, and describe them with the tools of sequence analysis. Firstly, our descriptive results show that employment patterns are generally not stable in time. At least a quarter of the employed population spends the whole time period in one state. Sequence diversity measured by an entropy index is shown to be high and quite stable. There is more female participation in large public sector organizations, and women have larger mean time in those organizations too. Men's participation and mean time is higher in private sector organizations and more equally distributed. A sequence clustering reveals four distinct groupings. One cluster is always dominated by full sequences in large organizations of the public sector. Secondly, we use the sequence clusters as input to quantify positive feedback effects on the likelihood for an employee to stay in an organization. We find indication for a positive feedback mechanism only in a limited number of cases, mainly at the beginning of the 1990s for large highly diverse public organizations. Gender differences exist but are not very pronounced.

Keyword [en]
organizational dynamics, employment careers, sequence analysis, social mechanism, positive feedback mechanism
National Category
Sociology
Research subject
Sociology
Identifiers
URN: urn:nbn:se:su:diva-139157OAI: oai:DiVA.org:su-139157DiVA: diva2:1071464
Available from: 2017-02-05 Created: 2017-02-03 Last updated: 2017-02-20Bibliographically approved
In thesis
1. Modeling Organizational Dynamics: Distributions, Networks, Sequences and Mechanisms
Open this publication in new window or tab >>Modeling Organizational Dynamics: Distributions, Networks, Sequences and Mechanisms
2017 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

The study of how social organizations work, change and develop is central to sociology and to our understanding of the social world and its transformations. At the same time, the underlying principles of organizational dynamics are extremely difficult to investigate. This is partly due to the difficulties of tracking organizations, individuals and their interactions over relatively long periods of time. But it is also due to limitations in the kinds of quantitative methods used to tackle these questions, which are for the most part based on regression analysis.

This thesis seeks to improve our understanding of social organizing by using models to explore and describe the logics of the structures and mechanisms underlying organizational change. Particular emphasis is given to the modeling process, the use of new concepts and analogies, and the application of interdisciplinary methods to get new insights into classical sociological questions.

The thesis consists of an introductory part and five studies (I-V). Using Swedish longitudinal data on employment in the Stockholm Region, the studies tackle different dimensions of organizational dynamics, from organizational structures and growth processes to labor mobility and employment trajectories. The introductory chapters contextualize the studies by providing an overview of theories, concepts and quantitative methods that are relevant for the modeling of organizational dynamics. 

The five studies look into various aspects of organizational dynamics with the help of complementary data representations and non-traditional quantitative methods. Study I analyzes organizational growth statistics for different sectors and industries. The typically observed heavy-tailed statistical patterns for the size and growth rate distributions are broken down into a superposition of interorganizational movements. Study II models interorganizational movements as a labor flow network. Organizations tend to be more tightly linked if they belong to the same ownership sector. Additionally, public organizations have a more stable connection structure. Study III uses a similarity-based method called homogeneity analysis to map out the social space of large organizations in the Stockholm Region. A social distance is then derived within this space, and we find that the interorganizational movements analyzed in Studies I and II take place more often between organizations that are closer in social space and in the same network community. Study IV presents an approach to organizational dynamics based on sequences of employment states. Evidence for a positive feedback mechanism is found for large and highly sequence-diverse public organizations. Finally, Study V features an agent-based model where we simulate a social influence mechanism for organizational membership dynamics. We introduce a parameter analogous to a physical temperature to model contextual influence, and the familiar growth distributions are recovered as an intermediate case between extreme parameter values.

The thesis as a whole provides suggestions for a more process-oriented modeling approach to social organizing that gives a more prominent role to the logics of organizational change. Finally, the series of methodological tools discussed can be useful for the analysis of many other social processes and more broadly for the development of quantitative sociological methods.

Place, publisher, year, edition, pages
Stockholm: Department of Sociology, Stockholm University, 2017. 101 p.
Series
Stockholm studies in sociology, ISSN 0491-0885 ; 67
Keyword
organizational dynamics, social organizing, organizational change, modeling, organizational growth, process stability, labor flow network, employment trajectories, heavy-tailed distributions, complex network analysis, sequence analysis, agent-based modeling, sociophysics
National Category
Sociology
Research subject
Sociology
Identifiers
urn:nbn:se:su:diva-139766 (URN)978-91-7649-673-2 (ISBN)978-91-7649-674-9 (ISBN)
Public defence
2017-03-31, hörsal 11, hus F, Universitetsvägen 10 F, Stockholm, 10:00 (English)
Opponent
Supervisors
Note

At the time of the doctoral defense, the following papers were unpublished and had a status as follows: Paper 1: Manuscript. Paper 2: Manuscript. Paper 3: Manuscript. Paper 4: Manuscript.

 

Available from: 2017-03-08 Created: 2017-02-13 Last updated: 2017-03-06Bibliographically approved

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